Quality versus quantity in scientific impact

TL;DR

This paper introduces a statistical baseline method to separate quality from quantity in citation metrics, enabling fairer comparisons of scientific impact across disciplines, career stages, and publication records.

Contribution

The authors propose a novel, flexible method that decouples quality and quantity in impact metrics, accounting for biases and enabling fair evaluations of researchers, journals, and institutions.

Findings

Captures Nobel laureates' quality regardless of publication count

Effectively suppresses discipline and career-stage biases

Analyzes impact across nearly a million scholars and thousands of journals

Abstract

Citation metrics are becoming pervasive in the quantitative evaluation of scholars, journals and institutions. More then ever before, hiring, promotion, and funding decisions rely on a variety of impact metrics that cannot disentangle quality from quantity of scientific output, and are biased by factors such as discipline and academic age. Biases affecting the evaluation of single papers are compounded when one aggregates citation-based metrics across an entire publication record. It is not trivial to compare the quality of two scholars that during their careers have published at different rates in different disciplines in different periods of time. We propose a novel solution based on the generation of a statistical baseline specifically tailored on the academic profile of each researcher. Our method can decouple the roles of quantity and quality of publications to explain how a certain level of impact is achieved. The method is flexible enough to allow for the evaluation of, and fair comparison among, arbitrary collections of papers --- scholar publication records, journals, and entire institutions; and can be extended to simultaneously suppresses any source of bias. We show that our method can capture the quality of the work of Nobel laureates irrespective of number of publications, academic age, and discipline, even when traditional metrics indicate low impact in absolute terms. We further apply our methodology to almost a million scholars and over six thousand journals to measure the impact that cannot be explained by the volume of publications alone.